{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import h5py\n",
    "import numpy as np \n",
    "from ripser import Rips, ripser\n",
    "from sklearn import preprocessing\n",
    "from scipy.spatial.distance import cdist, pdist, squareform\n",
    "from scipy.ndimage import gaussian_filter1d, gaussian_filter\n",
    "from scipy.stats import binned_statistic_2d, pearsonr\n",
    "from scipy.sparse import coo_matrix\n",
    "from scipy.linalg import eigh\n",
    "from scipy.sparse.linalg import lsmr\n",
    "from scipy import stats\n",
    "from datetime import datetime \n",
    "import time\n",
    "import functools\n",
    "from scipy import signal\n",
    "from scipy import optimize\n",
    "import sys\n",
    "import numba\n",
    "from utils import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "bRoll = False\n",
    "dim = 6\n",
    "ph_classes = [0,1] # Decode the ith most persistent cohomology class\n",
    "num_circ = len(ph_classes)\n",
    "dec_tresh = 0.99\n",
    "metric = 'cosine'\n",
    "maxdim = 1\n",
    "coeff = 47\n",
    "active_times = 15000\n",
    "k = 1000\n",
    "num_times = 5\n",
    "n_points = 1200\n",
    "nbs = 800\n",
    "sigma = 1500\n",
    "folder = 'Toroidal_topology_grid_cell_data//' # directory to data\n",
    "\n",
    "\n",
    "## Iterates over the different datasets\n",
    "for rat_name, mod_name, sess_name, day_name in (#('R', '1', 'OF', 'day1'),\n",
    "#                                                ('R', '2', 'OF', 'day1'),\n",
    "#                                                ('R', '3', 'OF', 'day1'),\n",
    "#                                                ('R', '1', 'WW', 'day1'),\n",
    "#                                                ('R', '2', 'WW', 'day1'),\n",
    "#                                                ('R', '3', 'WW', 'day1'),\n",
    "                                                ('R', '1', 'OF', 'day2'),\n",
    "#                                                ('R', '2', 'OF', 'day2'),\n",
    "#                                                ('R', '3', 'OF', 'day2'),\n",
    "#                                                ('R', '1', 'REM', 'day2'),\n",
    "#                                                ('R', '2', 'REM', 'day2'),\n",
    "#                                                ('R', '3', 'REM', 'day2'),\n",
    "#                                                ('R', '1', 'SWS', 'day2'),\n",
    "#                                                ('R', '2', 'SWS', 'day2'),\n",
    "#                                                ('R', '3', 'SWS', 'day2'),\n",
    "#                                                ('Q', '1', 'OF', ''),\n",
    "#                                                ('Q', '2', 'OF', ''),\n",
    "#                                                ('Q', '1', 'WW', ''),\n",
    "#                                                ('Q', '2', 'WW', ''),\n",
    "#                                                ('Q', '1', 'REM', ''),\n",
    "#                                                ('Q', '2', 'REM', ''),\n",
    "#                                                ('Q', '1', 'SWS', ''),\n",
    "#                                                ('Q', '2', 'SWS', ''),\n",
    "#                                                ('S', '1', 'OF', ''),\n",
    "#                                                ('S', '1', 'WW', ''),\n",
    "#                                                ('S', '1', 'REM', ''),\n",
    "#                                                ('S', '1', 'SWS', '')\n",
    "                                                ):\n",
    "    if sess_name in ('OF', 'WW'):\n",
    "        sspikes,__,__,__,__ = get_spikes(rat_name, mod_name, day_name, sess_name, bType = 'pure',\n",
    "                                         bSmooth = True, bSpeed = True, folder = folder )\n",
    "    else:\n",
    "        sspikes = get_spikes(rat_name, mod_name, day_name, sess_name, bType = 'pure', bSmooth = True, bSpeed = False, folder = folder)\n",
    "        \n",
    "    num_neurons = len(sspikes[0,:])\n",
    "\n",
    "    if bRoll:\n",
    "        np.random.seed(s)\n",
    "        shift = np.zeros(num_neurons, dtype = int)\n",
    "        for n in range(num_neurons):\n",
    "            shifti = int(np.random.rand()*len(sspikes[:,0]))\n",
    "            sspikes[:,n] = np.roll(sspikes[:,n].copy(), shifti)\n",
    "            shift[n] = shifti\n",
    "            \n",
    "    times_cube = np.arange(0,len(sspikes[:,0]),num_times)\n",
    "    movetimes = np.sort(np.argsort(np.sum(sspikes[times_cube,:],1))[-active_times:])\n",
    "    movetimes = times_cube[movetimes]\n",
    "\n",
    "    dim_red_spikes_move_scaled,__,__ = pca(preprocessing.scale(sspikes[movetimes,:]), dim = dim)\n",
    "    indstemp,dd,fs  = sample_denoising(dim_red_spikes_move_scaled,  k, \n",
    "                                        n_points, 1, metric)\n",
    "    dim_red_spikes_move_scaled = dim_red_spikes_move_scaled[indstemp,:]\n",
    "    X = squareform(pdist(dim_red_spikes_move_scaled, metric))\n",
    "    knn_indices = np.argsort(X)[:, :nbs]\n",
    "    knn_dists = X[np.arange(X.shape[0])[:, None], knn_indices].copy()\n",
    "    sigmas, rhos = smooth_knn_dist(knn_dists, nbs, local_connectivity=0)\n",
    "    rows, cols, vals = compute_membership_strengths(knn_indices, knn_dists, sigmas, rhos)\n",
    "    result = coo_matrix((vals, (rows, cols)), shape=(X.shape[0], X.shape[0]))\n",
    "    result.eliminate_zeros()\n",
    "    transpose = result.transpose()\n",
    "    prod_matrix = result.multiply(transpose)\n",
    "    result = (result + transpose - prod_matrix)\n",
    "    result.eliminate_zeros()\n",
    "    d = result.toarray()\n",
    "    d = -np.log(d)\n",
    "    np.fill_diagonal(d,0)\n",
    "\n",
    "    persistence = ripser(d, maxdim=maxdim, coeff=coeff, do_cocycles= True, distance_matrix = True)    \n",
    "    plot_barcode(persistence['dgms'])    \n",
    "    if len(day_name)>0:\n",
    "        day_name = '_' + day_name\n",
    "    print(rat_name + '_' + mod_name + '_' + sess_name + day_name )\n",
    "    plt.show()\n",
    "    \n",
    "    try:\n",
    "        os.mkdir(folder + 'Results')\n",
    "    except:\n",
    "        print('Results directory already created')\n",
    "    np.savez_compressed(folder + 'Results//' + \n",
    "        rat_name + '_' + mod_name + '_' + sess_name + day_name  + '_persistence', \n",
    "        persistence = persistence, indstemp = indstemp,  movetimes = movetimes)\n",
    "    day_name = day_name[1:]\n",
    "    \n",
    "    ############ Decode cocycles ################\n",
    "    diagrams = persistence[\"dgms\"] # the multiset describing the lives of the persistence classes\n",
    "    cocycles = persistence[\"cocycles\"][1] # the cocycle representatives for the 1-dim classes\n",
    "    dists_land = persistence[\"dperm2all\"] # the pairwise distance between the points \n",
    "    births1 = diagrams[1][:, 0] #the time of birth for the 1-dim classes\n",
    "    deaths1 = diagrams[1][:, 1] #the time of death for the 1-dim classes\n",
    "    deaths1[np.isinf(deaths1)] = 0\n",
    "    lives1 = deaths1-births1 # the lifetime for the 1-dim classes\n",
    "    iMax = np.argsort(lives1)\n",
    "    coords1 = np.zeros((num_circ, len(indstemp)))\n",
    "    threshold = births1[iMax[-2]] + (deaths1[iMax[-2]] - births1[iMax[-2]])*dec_tresh\n",
    "    for c in ph_classes:\n",
    "        cocycle = cocycles[iMax[-(c+1)]]\n",
    "        coords1[c,:],inds = get_coords(cocycle, threshold, len(indstemp), dists_land, coeff)\n",
    "\n",
    "    num_neurons = len(sspikes[0,:])\n",
    "    centcosall = np.zeros((num_neurons, 2, n_points))\n",
    "    centsinall = np.zeros((num_neurons, 2, n_points))\n",
    "    dspk = preprocessing.scale(sspikes[movetimes[indstemp],:])\n",
    "\n",
    "    for neurid in range(num_neurons):\n",
    "        spktemp = dspk[:, neurid].copy()\n",
    "        centcosall[neurid,:,:] = np.multiply(np.cos(coords1[:, :]*2*np.pi),spktemp)\n",
    "        centsinall[neurid,:,:] = np.multiply(np.sin(coords1[:, :]*2*np.pi),spktemp)\n",
    "\n",
    "    if sess_name in ('OF', 'WW'):\n",
    "        sspikes,xx,yy,aa,tt = get_spikes(rat_name, mod_name, day_name, sess_name, bType = 'pure',\n",
    "                                         bSmooth = True, bSpeed = True, smoothing_width = sigma, folder = folder)\n",
    "        spikes,__,__,__,__ = get_spikes(rat_name, mod_name, day_name, sess_name, bType = 'pure',\n",
    "                                         bSmooth = False, bSpeed = True, folder = folder)\n",
    "    else:\n",
    "        sspikes = get_spikes(rat_name, mod_name, day_name, sess_name, bType = 'pure', bSmooth = True, bSpeed = False,\n",
    "                             smoothing_width = sigma, folder = folder)\n",
    "        spikes = get_spikes(rat_name, mod_name, day_name, sess_name, bType = 'pure', bSmooth = False, bSpeed = False,\n",
    "                            folder = folder)\n",
    "\n",
    "    times = np.where(np.sum(spikes>0, 1)>=1)[0]\n",
    "    dspk = preprocessing.scale(sspikes)\n",
    "    sspikes = sspikes[times,:]\n",
    "    dspk = dspk[times,:]\n",
    "\n",
    "    a = np.zeros((len(sspikes[:,0]), 2, num_neurons))\n",
    "    for n in range(num_neurons):\n",
    "        a[:,:,n] = np.multiply(dspk[:,n:n+1],np.sum(centcosall[n,:,:],1))\n",
    "\n",
    "    c = np.zeros((len(sspikes[:,0]), 2, num_neurons))\n",
    "    for n in range(num_neurons):\n",
    "        c[:,:,n] = np.multiply(dspk[:,n:n+1],np.sum(centsinall[n,:,:],1))\n",
    "\n",
    "    mtot2 = np.sum(c,2)\n",
    "    mtot1 = np.sum(a,2)\n",
    "    coords = np.arctan2(mtot2,mtot1)%(2*np.pi)\n",
    "    if sess_name == 'OF':\n",
    "        coordsbox = coords.copy()\n",
    "        times_box = times.copy()\n",
    "    else:\n",
    "        sspikes,xx,yy,aa,tt = get_spikes(rat_name, mod_name, day_name, 'OF', bType = 'pure',\n",
    "                                         bSmooth = True, bSpeed = True, smoothing_width = sigma, folder = folder)\n",
    "        spikes,__,__,__,__ = get_spikes(rat_name, mod_name, day_name, 'OF', bType = 'pure',\n",
    "                                         bSmooth = False, bSpeed = True, folder = folder)\n",
    "        dspk =preprocessing.scale(sspikes)\n",
    "        times_box = np.where(np.sum(spikes>0, 1)>=1)[0]\n",
    "        dspk = dspk[times_box,:]\n",
    "\n",
    "        a = np.zeros((len(times_box), 2, num_neurons))\n",
    "        for n in range(num_neurons):\n",
    "            a[:,:,n] = np.multiply(dspk[:,n:n+1],np.sum(centcosall[n,:,:],1))\n",
    "\n",
    "        c = np.zeros((len(times_box), 2, num_neurons))\n",
    "        for n in range(num_neurons):\n",
    "            c[:,:,n] = np.multiply(dspk[:,n:n+1],np.sum(centsinall[n,:,:],1))\n",
    "\n",
    "        mtot2 = np.sum(c,2)\n",
    "        mtot1 = np.sum(a,2)\n",
    "        coordsbox = np.arctan2(mtot2,mtot1)%(2*np.pi)\n",
    "    plot_times = np.arange(0, len(times_box), 10)\n",
    "    plt.viridis()\n",
    "    fig, ax = plt.subplots(1,2)\n",
    "    ax[0].axis('off')\n",
    "    ax[0].scatter(xx[times_box][plot_times], yy[times_box][plot_times], c = np.cos(coordsbox[plot_times,0]))\n",
    "    ax[0].set_aspect('equal', 'box')\n",
    "    \n",
    "    ax[1].axis('off')\n",
    "    ax[1].scatter(xx[times_box][plot_times], yy[times_box][plot_times], c = np.cos(coordsbox[plot_times,1]))\n",
    "    ax[1].set_aspect('equal', 'box')\n",
    "\n",
    "    if len(day_name)>0:\n",
    "        day_name = '_' + day_name\n",
    "    np.savez_compressed(folder + 'Results//' + \n",
    "                        rat_name + '_' + mod_name + '_' + sess_name + day_name  + '_decoding', \n",
    "                        coords = coords, coordsbox = coordsbox,  times = times, \n",
    "                        times_box = times_box, centcosall = centcosall, centsinall = centsinall)\n",
    "\n"
   ]
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